Document Detail

Adjusting the effect of nonstationarity in cluster-based and TFCE inference.
MedLine Citation:
PMID:  20955803     Owner:  NLM     Status:  MEDLINE    
In nonstationary images, cluster inference depends on the local image smoothness, as clusters tend to be larger in smoother regions by chance alone. In order to correct the inference for such nonstationary, cluster sizes can be adjusted according to a local smoothness estimate. In this study, adjusted cluster sizes are used in a permutation-testing framework for both cluster-based and threshold-free cluster enhancement (TFCE) inference and tested on both simulated and real data. We find that TFCE inference is already fairly robust to nonstationarity in the data, while cluster-based inference requires an adjustment to ensure homogeneity. A group of possible multi-level adjustments are introduced and their results on simulated and real data are assessed using a new performance index. We also find that adjusting for local smoothness via a separate resampling procedure is more effective at removing nonstationarity than an adjustment via a random field theory based smoothness estimator.
Gholamreza Salimi-Khorshidi; Stephen M Smith; Thomas E Nichols
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2010-10-16
Journal Detail:
Title:  NeuroImage     Volume:  54     ISSN:  1095-9572     ISO Abbreviation:  Neuroimage     Publication Date:  2011 Feb 
Date Detail:
Created Date:  2010-12-21     Completed Date:  2011-03-31     Revised Date:  2014-02-20    
Medline Journal Info:
Nlm Unique ID:  9215515     Medline TA:  Neuroimage     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2006-19     Citation Subset:  IM    
Copyright Information:
Copyright © 2010 Elsevier Inc. All rights reserved.
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MeSH Terms
Alzheimer Disease / pathology
Brain / anatomy & histology,  pathology
Brain Mapping / statistics & numerical data*
Cluster Analysis*
Cognition Disorders / pathology
Computer Simulation
Data Interpretation, Statistical
False Positive Reactions
Image Processing, Computer-Assisted / statistics & numerical data*
Linear Models
Magnetic Resonance Imaging / statistics & numerical data
Normal Distribution
ROC Curve
Reproducibility of Results
Grant Support
G0700399//Medical Research Council; G0900908//Medical Research Council

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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